Exploring Human Brain Metabolism via Genome-Scale Metabolic Modeling with Highlights on Multiple Sclerosis.

Area of Science:

• Neuroscience
• Systems Biology
• Metabolic Engineering

Background:

• Cerebral dysfunctions cause neurological diseases due to brain complexity.
• Genome-scale metabolic models (GEMs) are crucial for understanding cellular metabolism.

Purpose of the Study:

• To reconstruct brain cell-specific GEMs and integrate them into a comprehensive model.
• To predict metabolic alterations in the human brain under various conditions and in disease.

Main Methods:

• Reconstructed cell-specific GEMs for neurons, astrocytes, microglia, and oligodendrocytes using single-cell RNA-seq and the tINIT algorithm.
• Integrated these models and added intercellular reactions to create the iHumanBrain2690 model.
• Analyzed metabolic alterations related to glucose, ketone bodies, oxygen, and reporter metabolites.

Main Results:

• Glucose supplementation enhanced glycolysis; ketone bodies boosted TCA cycle and oxidative phosphorylation.
• Identified L-carnitine and arachidonate as key reporter metabolites in microglia in multiple sclerosis.
• Carbamoyl-phosphate was identified as a top reporter metabolite in primary progressive multiple sclerosis.

Conclusions:

• The iHumanBrain2690 model provides insights into brain metabolism in health and disease.
• This network aids in understanding complex metabolic pathways and their role in neurological disorders.